| SO-MI: A surrogate model algorithm for computationally expensive nonlinear mixed-integer black-box global optimization problems J Müller, CA Shoemaker, R Piché Computers & Operations Research 40 (5), 1383-1400, 2013 | 198 | 2013 |
| Influence of Ensemble Surrogate Models and Sampling Strategy on the Solution Quality of Algorithms for Computationally Expensive Black-Box Global Optimization Problems J Müller, CA Shoemaker Journal of Global Optimization 60 (2), 123-144, 2014 | 163 | 2014 |
| Mixture surrogate models based on Dempster-Shafer theory for global optimization problems J Müller, R Piché Journal of Global Optimization 51, 79-104, 2011 | 103 | 2011 |
| MISO: mixed-integer surrogate optimization framework J Müller Optimization and Engineering, 2015 | 77 | 2015 |
| Classical optimizers for noisy intermediate-scale quantum devices W Lavrijsen, A Tudor, J Müller, C Iancu, W De Jong 2020 IEEE international conference on quantum computing and engineering (QCE …, 2020 | 74 | 2020 |
| SO-I: A Surrogate Model Algorithm for Expensive Nonlinear Integer Programming Problems Including Global Optimization Applications J Müller, CA Shoemaker, R Piche Journal of Global Optimization 59 (4), 865-889, 2014 | 70 | 2014 |
| Approximative solutions to the bicriterion vehicle routing problem with time windows J Müller European Journal of Operational Research 202 (1), 223-231, 2010 | 63 | 2010 |
| SOCEMO: surrogate optimization of computationally expensive multiobjective problems J Müller INFORMS Journal on Computing 29 (4), 581-596, 2017 | 62 | 2017 |
| MATSuMoTo: The MATLAB surrogate model toolbox for computationally expensive black-box global optimization problems J Mueller arXiv preprint arXiv:1404.4261, 2014 | 59 | 2014 |
| Surrogate optimization of deep neural networks for groundwater predictions J Müller, J Park, R Sahu, C Varadharajan, B Arora, B Faybishenko, ... Journal of Global Optimization 81, 203-231, 2021 | 50 | 2021 |
| GOSAC: global optimization with surrogate approximation of constraints J Müller, JD Woodbury Journal of Global Optimization 69 (1), 117-136, 2017 | 36 | 2017 |
| CH4 Parameter Estimation in CLM4.5bgc Using Surrogate Global Optimization J Muller, R Paudel, CA Shoemaker, J Woodbury, Y Wang, N Mahowald Geoscientific Model Development 8 (10), 3285-3310, 2015 | 29 | 2015 |
| User guide for modularized surrogate model toolbox J Müller Tampere University of Technology, 2012 | 28 | 2012 |
| Surrogate optimization of computationally expensive black-box problems with hidden constraints J Müller, M Day INFORMS Journal on Computing 31 (4), 689-702, 2019 | 23 | 2019 |
| Impact of input feature selection on groundwater level prediction from a multi-layer perceptron neural network RK Sahu, J Müller, J Park, C Varadharajan, B Arora, B Faybishenko, ... Frontiers in Water 2, 573034, 2020 | 18 | 2020 |
| Surrogate model algorithms for computationally expensive black-box global optimization problems J Müller Tampere University of Technology, 2012 | 18 | 2012 |
| An efficient algorithm for automatic structure optimization in x-ray standing-wave experiments O Karslıoğlu, M Gehlmann, J Müller, S Nemšák, JA Sethian, A Kaduwela, ... Journal of Electron Spectroscopy and Related Phenomena 230, 10-20, 2019 | 13 | 2019 |
| Adaptive Gaussian process surrogates for Bayesian inference T Takhtaganov, J Müller arXiv preprint arXiv:1809.10784, 2018 | 12 | 2018 |
| Characterization of free-standing InAs quantum membranes by standing wave hard x-ray photoemission spectroscopy G Conti, S Nemšák, CT Kuo, M Gehlmann, C Conlon, A Keqi, ... APL materials 6 (5), 058101, 2018 | 12 | 2018 |
| Cosmic inference: Constraining parameters with observations and a highly limited number of simulations T Takhtaganov, Z Lukić, J Müller, D Morozov The Astrophysical Journal 906 (2), 74, 2021 | 10 | 2021 |
Robert PicheTampere University of TechnologyVerified email at tuni.fi
